RAG System
Specialized search and Q&A system for gaming internal resources — dialogues, items, regional lore. Vectorizing unstructured game data into a Vector Database to enable LLMs to provide context-aware responses.
Cloud Services professional focused on data center stability and core infrastructure. Combining self-taught programming with AI integration to deliver technical excellence.
Specialized search and Q&A system for gaming internal resources — dialogues, items, regional lore. Vectorizing unstructured game data into a Vector Database to enable LLMs to provide context-aware responses.
Diagnostic tool for measuring retrieval performance and visualizing vectorized data using Three.js — a crucial component for RAG system quality assurance.
Personalized AI assistant inspired by Neuro-sama and Sovits_GPT, focused on local execution (≤ 8B models). Fine-tuning English models for enhanced Korean proficiency with voice interaction.
Information aggregation tool for tracking Economics, Society, Politics, and Diplomacy trends. Future roadmap: integrating AI Agents for autonomous intelligence categorization and summarization.
Developed a beef quality classification model. Successfully improved accuracy from 50% to 89% through optimization and data analysis.
Committed to stable data center server management and high-availability network operations.
Rapidly acquiring new technologies and internalizing operational manuals for proactive task execution.
Systematic management of data powering AI. Bridging existing tools and groundbreaking implementation.